Put AI to work in your organization, on terms you control.
Liteseed helps small organizations and professional firms adopt AI properly: deciding where it fits, choosing and setting up the right tools, writing the policy that governs them, automating the work that eats staff time, and running private AI on Canadian infrastructure for the data that must not leave your control. The applications and servers underneath are built and looked after by the same people.
From "should we use AI?" to AI that runs every day, with one team seeing it through.
Most organizations already use AI somewhere, usually without a plan, a policy or anyone checking where the data goes. We start from where you are: what your people use today, what your obligations are, and which work is worth automating. That work is easy to spot: it repeats, it's slow, it's where mistakes happen, and it grows with the business without needing another hire. Then we set it up, train your staff, and keep it running.
AI readiness and strategy
A short, plain-language review before anything is bought. We inventory the AI your staff already use, approved or not, take a fair look at the AI built into software you already pay for (Microsoft 365 Copilot, your practice-management, CRM or accounting system) and say whether to keep, configure, add or drop it, map where your data flows against your privacy and professional obligations, rank the processes worth automating first, and hand you a 90-day roadmap. If the right answer is the tool you already have, we say so.
An AI-use policy your people can actually follow, written for how your organization works rather than copied from a template: what may go into which tool, when clients are told, who reviews output, and what gets logged. For the private workspace we build the access controls and audit trails to match. For your commercial tools we tell you what to switch on and what to check, and we review the policy as tools and rules change. Documentation you can show a client, an insurer or a regulator.
For the work that must not leave your control: a private AI workspace running open-weight language models on Canadian-owned servers or on a machine in your office, with single sign-on, document search and question-answering over your own files, templates and past work, and logging of every request. The same containers run on-site, on our Canadian host or on Canadian GPU cloud, so moving between them is a redeploy, not a rebuild. Nothing you put into it is sent to, or available to, a foreign provider, and nothing is used to train anyone's model.
Local models · audit logging · on-site servers · Canadian hosting
Automation, workflow and agents
Moving business processes into AI, one step at a time: client or customer intake from first contact to an opened file, document assembly from your own templates and precedents, routing between email, your line-of-business systems and accounting, and the reporting nobody has time to do. Every workflow has a human checkpoint where it matters, and agents that act on their own come only after the workflows under them have run reliably for a while. We measure the hours before and after, so the payoff is counted rather than promised: time back, fewer errors, and work that grows without another hire.
n8n · intake · document assembly · integrations · AI agents · human review
Managed AI service
AI is not a one-time install. On a monthly retainer we host, patch and monitor the private workspace, upgrade models as better ones arrive, manage access to it, and build the next automation. We also govern how your commercial AI tools are used, without administering them: regular access reviews, checks that actual use matches your policy and intent, and a watch on vendor changes. A quarterly report covers usage and compliance across both, with any fixes carried out by your own team or IT provider.
Maintenance · quarterly report · model upgrades · monitoring
Applications and servers
The foundation AI runs on, and work we have done since 2004: secure websites and small web applications your team can update, Linux servers and virtualization set up properly the first time, tested backups, monitoring that tells you before users do, and networks with sensible segments. On a Canadian provider, global cloud, or a box in your office.
PHP · Python · Linux · Virtual Machines · Data centres
Approach
Your data stays in Canada, and you keep the keys.
Canadian by default
Sensitive work runs on servers in Canada owned by Canadians, or on hardware you own. A Canadian region of a US cloud is still subject to US law, and a data processing agreement with a foreign provider is not the same as your data being here. We say plainly what each setup does and doesn't protect.
Hybrid, not all-or-nothing
Most organizations end up with both: commercial AI tools, set up and governed under a written policy, for everyday work, and a private workspace for the files that must not leave your control. We don't ask you to abandon the software you already run; we connect to it and draw the line in the right place.
Independent of vendors
We don't represent any AI product, so the recommendation starts from what fits your organization. Sometimes that's the tool you already pay for, configured properly. We won't pitch a model's cleverness: we show it working on your own documents and workflows before you commit.
Open tools, written down
We build on open-source software you could hire anyone to maintain, and every job ends with documentation a capable person can follow: what was built, where it lives, who has access, and how to restore it from backup. You get the passwords, the configuration and the notes.
About
Two decades of building systems that stay up, now applied to AI.
Liteseed's work today is AI: helping organizations adopt it safely, automating the work that doesn't need a person, and running it privately where the data demands. Most AI agencies can't run infrastructure, and most IT providers can't run AI. We do both, which is what makes a private workspace, a clear policy for the commercial tools you use and the automation between them one plan rather than three vendors.
The company was founded in Victoria in 2004 and has built large public web deployments, custom applications and embedded hardware systems along the way, which is why the applications and servers underneath the AI get the same care. All technical work is led by founder Phillip Jubb, who brings more than 30 years of hands-on experience in software, servers and production systems. Most of that was as a solutions architect and senior leader in public healthcare, where privacy laws are some of the strictest in Canada. That background shapes how we build: privacy and security are designed in from the start, not added at the end. You're required to protect your data; our systems make that the default.
Founded2004
Technical leadPhillip Jubb
Experience30+ years hands-on
LocationVictoria, BC · remote across Canada
Contact
Tell us what you're working on.
A couple of sentences is plenty: what your people use today, what you're unsure about, and what you'd like AI to take off their plate. Every message is read and answered by the people who would do the work, not a sales team.